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--- |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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base_model: facebook/mms-1b-all |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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- bleu |
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model-index: |
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- name: wav2vec2-mms-1b-CV17.0-training_set_variations |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: common_voice_17_0 |
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type: common_voice_17_0 |
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config: ta |
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split: validation |
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args: ta |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.45588302699729566 |
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- name: Bleu |
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type: bleu |
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value: 0.30120570288375 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# wav2vec2-mms-1b-CV17.0-training_set_variations |
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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4242 |
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- Wer: 0.4559 |
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- Cer: 0.0764 |
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- Bleu: 0.3012 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.001 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.15 |
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- training_steps: 2000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Bleu | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:| |
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| 13.1596 | 12.5 | 50 | 6.8694 | 1.0 | 0.9625 | 0.0 | |
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| 3.2131 | 25.0 | 100 | 0.4085 | 0.4707 | 0.0784 | 0.2830 | |
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| 0.1719 | 37.5 | 150 | 0.2583 | 0.3920 | 0.0650 | 0.3818 | |
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| 0.0962 | 50.0 | 200 | 0.2869 | 0.4118 | 0.0682 | 0.3547 | |
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| 0.0648 | 62.5 | 250 | 0.3209 | 0.4213 | 0.0696 | 0.3435 | |
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| 0.0613 | 75.0 | 300 | 0.3404 | 0.4454 | 0.0742 | 0.3200 | |
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| 0.0515 | 87.5 | 350 | 0.3744 | 0.4385 | 0.0734 | 0.3289 | |
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| 0.0426 | 100.0 | 400 | 0.3835 | 0.4479 | 0.0748 | 0.3078 | |
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| 0.0384 | 112.5 | 450 | 0.3776 | 0.4432 | 0.0746 | 0.3243 | |
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| 0.0363 | 125.0 | 500 | 0.4053 | 0.4371 | 0.0732 | 0.3251 | |
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| 0.0385 | 137.5 | 550 | 0.4225 | 0.4520 | 0.0772 | 0.3115 | |
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| 0.0343 | 150.0 | 600 | 0.4295 | 0.4463 | 0.0758 | 0.3167 | |
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| 0.0371 | 162.5 | 650 | 0.4242 | 0.4559 | 0.0764 | 0.3012 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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